A science-based approach could reduce both acute and Intensive Care Unit (ICU) hospital admissions caused by Covid-19 in Qatar by more than 75%, a healthcare expert from Qatar Foundation (QF) has highlighted.
"Scientific analyses were conducted to prepare the country, even before the first case of community transmission was reported," explained Dr Laith Abu-Raddad from QF partner university Weill Cornell Medicine-Qatar.
“The key to Qatar’s resilience in the face of an extraordinary year was its ability to think and look ahead,” pointed out the expert in an article on QF website.
According to Dr Abu-Raddad, Qatar based its estimates on science-based epidemiological approaches and mathematical models in order to respond to the pandemic – including forecasting the impact of social and physical distancing restrictions.
“One of the first analyses was focused on forecasting healthcare needs in the country and looking for a potential impact of social and physical expensing restrictions by forecasting healthcare, I mean acute care, Intensive Care Unit beds, hospital admissions.
"The forecasts were quite close to what evolved eventually. So the country was able to prepare well for what was coming, and at no time was the health system overwhelmed or even near its threshold,” explained, Dr Abu-Raddad while addressing a virtual summit organised by QF member, Sidra Medicine.
From the very beginning of the pandemic, Qatar had chosen a path of epidemic suppression to flatten the curve as much as possible, recalled the expert.
“The mathematical model is still being used to monitor, track and forecast the progression of the epidemic,” he said. “One of the most important uses of modelling these days is to monitor the effective reproduction number of the virus or what we call Rt – which is a key measure of how fast the virus is growing.
“This will tell us whether there is a second wave coming, and so far, we do not see any imminent signs of a second wave for Qatar, because Rt continues to be, on average, below one. One of the most consequential applications of mathematical modelling has been the timing and manner of easing of restrictions.”
“The country’s leadership wanted to ease restrictions in such a way that we can achieve two things,” Dr Abu-Raddad continued. “The first one was to avoid a second wave as much as possible, because of the health consequences and the damage to the country's economic and social activity. And the second was to try to avoid an intermittent application of restrictions, because these will also harm stability.”
With these two conditions in mind, mathematical modelling was used to predict the easing of restrictions so that these goals could be achieved.
“It was predicted that the earliest day we could ease restrictions was June 15 – which was exactly what happened. This would allow us to have stability and functionality. And also, we would not need an intermittent application of restrictions. I considered this quite a triumph, because the decision to ease restrictions and the exact day was done based purely on science,” he maintained.
Besides the mathematical modelling methodologies that were part of the national response, Qatar also invested in major epidemiologic studies to understand the infection’s epidemiology and to further support the country’s response.
A centralised database system for everything Covid-19-related was used by researchers. They were able to assess the whole population in terms of infection and reinfection. “We looked at the risk of reinfection in the full cohort of those who have a PCR confirmed infection, and through this study, were able to confirm several reinfections,” pointed, Dr Abu-Raddad.